Formal security models

V. L. Tokarev

Čebyševskij sbornik, Tome 22 (2021) no. 1, pp. 488-494.

Résumé

In paper describes an approach to building a formal model of information security based on the use of predicate algebra. The model is represented as a decision tree. The algorithm of its construction based on the deductive method of searching for answers is developed and investigated.

Détail

Keywords: predicate algebra, formal models, information security.

Bibliographie

[1] ISO/1EC 15408-1: 2009 - Evaluation criteria for IT security - Part 1: Introduction and general model

[2] Devyanin P.N., “O razrabotke modelei bezopasnosti informatsionnykh potokov v kompyuternykh sistemakh s rolevym upravleniem dostupom”, Materialy 3-ei mezhdunarodnoi nauchnoi konferentsii po problemam bezopasnosti i protivodeistviya terrorizmu (MGU im. M.V. Lomonosova. 25–27 oktyabrya 2007 g.), MTsNMO, M., 2008, 261–265

[3] Devyanin P.N., “Problema obosnovaniya adekvatnosti formalnykh modelei bezopasnosti logicheskogo upravleniya dostupom i ikh realizatsii v kompyuternykh sistemakh”, Sistemy vysokoi dostupnosti, 2012, no. 2, 45–49

[4] Olifer V.G., Olifer N.A., Kompyuternye seti. Printsipy, tekhnologii, protokoly, Piter, SPb., 2011, 944 pp.

[5] Quinlan J. R., “Induction of Decision Trees”, Machine Learning, 1 (1986), 81–106 | MR

[6] Kashnitsky Y. S., “Methods of the search of accurate and interpretable rules for classifying data with complex structure”, XV artificial intelligence conference KII-2016, Proceedings of the conference, in 3-t. (Smolensk, Russia), Publishing House «Universum», Smolensk, 2016, 183–191

[7] Quinlan J. R., “Probabilistic decision trees”, Machine Learning. An Artificial Intelligence Approach III, eds. Y. Kodratoff, R. Michalski, Morgan Kaufmann Publishers, Inc, 1990, 140–152

[8] J. W. Grzymala-Busse, “Selected Algorithms of Machine Learning from Examples”, Iterative Dichotomizer, 3 (1993) | Zbl

[9] Taggart A.J., DeSimone A.M., Shih J.S., Filloux M.E., Fairbrother W.G., “Large-scale mapping of branchpoints in human transcripts in vivo”, Nature Structural and Molecular Biology, 2012, 719–721 | DOI

[10] Quinlan J. R., “Learning With Continuous Classes”, Proceedings of the 5th Australian Joint Conference on Artificial Intelligence, 1992, 343–348

[11] Quinlan J. R., C4.5 Programs for Machine Learning, Morgan Kaufmann, San Mateo, California, 1993

[12] Quinlan J.R., “Improved Use of Continuous Attributes in C4.5”, Journal of Artificial Intelligence Research, 4 (1996), 77–90 | DOI | Zbl

[13] Breiman L., Friedman J.H., Olshen R.A., Stone C.T., Classification and Regression Trees, Wadsworth, Belmont, California, 1984 | MR | Zbl

[14] D. Michie, D.J. Spiegelhalter, C.C. Taylor (eds.), “Machine Learning, Neural and Statistical Classification”, Journal of the American Statistical Association, 1994

[15] Marzinotto A., Colledanchise M., Smith C., Ögren P., “Towards a Unified BTs Framework for Robot Control”, Robotics and Automation (ICRA), 2014 IEEE International Conference, 2014

[16] Colledanchise M., Ögren P., Michele C., Petter O., Behavior Trees in Robotics and AI, 2018, arXiv: 1709.00084 | DOI

[17] Ögren P., “Increasing Modularity of UAV Control Systems using Computer Game Behavior Trees”, AIAA Guidance, Navigation and Control Conference (Minneapolis, Minnesota, 2012), 13–16 | MR | Zbl

[18] Klöckner A., “Behavior Trees for UAV Mission Management”, GI-Jahrestagung, 2013, 57–68